基于OpenCV的交通流实时检测研究

Z. Lei, Zhang Xue-fei, Liu Yin-ping
{"title":"基于OpenCV的交通流实时检测研究","authors":"Z. Lei, Zhang Xue-fei, Liu Yin-ping","doi":"10.1109/CSSE.2008.872","DOIUrl":null,"url":null,"abstract":"A vehicle detection algorithm was proposed based on the morphology and wavelet transform, in the context of the traditional difference. First, the background model was established, using statistical means of the rapid sequence. As background to transform the impact of light obviously, the corresponding easy and quick to update the background algorithm was used. Using the background of the video images to do background subtraction, and then images of the vehicles were accurate detection of mathematical morphology and wavelet transform. A video vehicle detection system was developed using visual C++6.0 and OpenCV image and development kits. A highway traffic flow has been detected by a background extraction, image filtering, image binary, morphological transformation, vehicle detection and segmentation methods and steps. To achieve some highway traffic flow analysis, results showed that: the system to identify the correct rate of more than 98 percent, satisfying the requirements of practical applications.","PeriodicalId":6460,"journal":{"name":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"43 1","pages":"870-873"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Research of the Real-Time Detection of Traffic Flow Based on OpenCV\",\"authors\":\"Z. Lei, Zhang Xue-fei, Liu Yin-ping\",\"doi\":\"10.1109/CSSE.2008.872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A vehicle detection algorithm was proposed based on the morphology and wavelet transform, in the context of the traditional difference. First, the background model was established, using statistical means of the rapid sequence. As background to transform the impact of light obviously, the corresponding easy and quick to update the background algorithm was used. Using the background of the video images to do background subtraction, and then images of the vehicles were accurate detection of mathematical morphology and wavelet transform. A video vehicle detection system was developed using visual C++6.0 and OpenCV image and development kits. A highway traffic flow has been detected by a background extraction, image filtering, image binary, morphological transformation, vehicle detection and segmentation methods and steps. To achieve some highway traffic flow analysis, results showed that: the system to identify the correct rate of more than 98 percent, satisfying the requirements of practical applications.\",\"PeriodicalId\":6460,\"journal\":{\"name\":\"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"volume\":\"43 1\",\"pages\":\"870-873\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSSE.2008.872\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSSE.2008.872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

摘要

在传统差分方法的基础上,提出了一种基于形态学和小波变换的车辆检测算法。首先,利用快速序列的统计方法建立背景模型;由于背景变换对光线的影响明显,因此采用了相应的简单快速的背景更新算法。利用视频图像的背景进行背景相减,然后对图像中的车辆进行数学形态学和小波变换的精确检测。利用visual c++ 6.0和OpenCV图像及开发工具开发了视频车辆检测系统。本文介绍了高速公路交通流检测的主要方法和步骤,包括背景提取、图像滤波、图像二值化、形态变换、车辆检测和分割等。以某高速公路交通流分析为例,结果表明:系统识别正确率达98%以上,满足实际应用要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Research of the Real-Time Detection of Traffic Flow Based on OpenCV
A vehicle detection algorithm was proposed based on the morphology and wavelet transform, in the context of the traditional difference. First, the background model was established, using statistical means of the rapid sequence. As background to transform the impact of light obviously, the corresponding easy and quick to update the background algorithm was used. Using the background of the video images to do background subtraction, and then images of the vehicles were accurate detection of mathematical morphology and wavelet transform. A video vehicle detection system was developed using visual C++6.0 and OpenCV image and development kits. A highway traffic flow has been detected by a background extraction, image filtering, image binary, morphological transformation, vehicle detection and segmentation methods and steps. To achieve some highway traffic flow analysis, results showed that: the system to identify the correct rate of more than 98 percent, satisfying the requirements of practical applications.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Isolate-Set-Based In-Memory Parallel Subgraph Matching Framework A Fast Attitude Estimation Method Using Homography Matrix IOT for smart farm: A case study of the Lingzhi mushroom farm at Maejo University Analyzing user reviews in Thai language toward aspects in mobile applications Front-rear crossover: A new crossover technique for solving a trap problem
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1